Plot

EDA Plot for each crop data

# Plotting the Value over Years for a specific Item, loop for all items
# change y aixs as unit is different for each Element Value
for (item in unique(data_fao$Item)) {
  plot <- ggplot(data = data_fao %>% filter(Item == item), aes(x = Year, y = Value, color = Element)) +
    geom_line() +
    labs(title = paste("Trends Over Time for", item), x = "Year", y = "Value")
  #print(plot)
  # Plotting the Value over Years for each Element (e.g., "Apples")
  options(repr.plot.width = 35, repr.plot.height = 8)  # Adjust width and height
  facet_plot <- ggplot(data = data_fao %>% filter(Item == item), aes(x = Year, y = Value)) +
    geom_line() +
    facet_wrap(~ Element, scales = "free_y") +
    labs(title = paste("Trends Over Time for", item), x = "Year", y = "Value") +
    theme_minimal()+
    scale_x_continuous(breaks = seq(min(data_fao$Year), max(data_fao$Year), by = 3))+
    theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))  # Rotate x-axis labels
# Change 'by' to your preferred interval

  print(facet_plot)
  }

## [1] "Adding columns for year and week"
## # A tibble: 6,609 × 5
## # Groups:   Year [127]
##     Year  Week week_Mean_Temperature week_Mean_Percentile_95 week_Mean_EHF_95
##    <dbl> <dbl>                 <dbl>                   <dbl>            <dbl>
##  1  1899     9                 0.925                    6.03           NaN   
##  2  1899    10                 4.59                     6.82           NaN   
##  3  1899    11                 1.86                     7.38           NaN   
##  4  1899    12                 1.87                     8.71           NaN   
##  5  1899    13                 3.91                    10.1             -8.19
##  6  1899    14                 5.99                    11.1            -14.3 
##  7  1899    15                 6.26                    12.0            -13.2 
##  8  1899    16                 8.11                    13.4            -14.1 
##  9  1899    17                 7.77                    14.3            -10.2 
## 10  1899    18                 7.53                    15.4            -13.0 
## # ℹ 6,599 more rows

linear reg for yield VS EHF 95

Abbotsford

## [1] "There are 47  NA in the matrix X in Abbotsford station"
## [1] "Results for crop: Apples"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -57270 -10358   2532  12719  50521 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 344369.8    89677.0   3.840  0.00495 **
## Week_9       -3993.2    10247.8  -0.390  0.70695   
## Week_10        321.9     5583.2   0.058  0.95544   
## Week_11       -389.8     8027.6  -0.049  0.96246   
## Week_12       -580.3     6797.0  -0.085  0.93406   
## Week_13      -9676.1    10926.5  -0.886  0.40169   
## Week_14       7807.3     8638.4   0.904  0.39250   
## Week_15       8572.3     7632.7   1.123  0.29397   
## Week_16       2343.9     6596.7   0.355  0.73154   
## Week_17      -5542.3     9669.5  -0.573  0.58228   
## Week_18        996.9     6208.4   0.161  0.87642   
## Week_19       7751.4     4517.8   1.716  0.12455   
## Week_20       2900.8     7820.3   0.371  0.72032   
## Week_21       2987.8     6425.2   0.465  0.65432   
## Week_22      -1442.2     5387.7  -0.268  0.79571   
## Week_23      -1061.5     7151.6  -0.148  0.88567   
## Week_24       2263.4     6361.1   0.356  0.73118   
## Week_25      -4939.7     5872.9  -0.841  0.42472   
## Week_26       1487.9     2184.6   0.681  0.51504   
## Week_27       1513.8     7205.9   0.210  0.83886   
## Week_28       4954.8     5231.6   0.947  0.37132   
## Week_29       1247.1     9404.0   0.133  0.89777   
## Week_30       -967.9     6450.5  -0.150  0.88444   
## Week_31       9042.4     8957.1   1.010  0.34228   
## Week_32     -12285.3     9112.1  -1.348  0.21451   
## Week_33      -2887.7     9568.6  -0.302  0.77051   
## Week_34      45568.4    16260.1   2.802  0.02311 * 
## Week_35     -13289.3    10436.2  -1.273  0.23863   
## Week_36       1006.6    10633.8   0.095  0.92691   
## Week_37       6034.8    11814.8   0.511  0.62330   
## Week_38       1277.1     9477.2   0.135  0.89614   
## Week_39       3552.7     8812.1   0.403  0.69739   
## Week_40      -7237.7     8644.6  -0.837  0.42675   
## Week_41      -8826.3     9972.4  -0.885  0.40194   
## Week_42       4938.5    12215.7   0.404  0.69660   
## Week_43      -6929.2    11284.7  -0.614  0.55625   
## Week_44       3205.8     5255.3   0.610  0.55877   
## Week_45     -13801.8    10998.4  -1.255  0.24494   
## Week_46      10228.2    11515.2   0.888  0.40033   
## Week_47      -6540.1     5890.4  -1.110  0.29913   
## Week_48       1976.9     8615.8   0.229  0.82428   
## Week_49       5893.4     5511.3   1.069  0.31612   
## Week_50       2325.6     5148.6   0.452  0.66348   
## Week_51      -4625.2     4880.3  -0.948  0.37102   
## Week_52       6727.5     5808.0   1.158  0.28015   
## Week_53      -7932.1     5241.0  -1.513  0.16862   
## Week_1        1757.7     5383.5   0.327  0.75242   
## Week_2       -6339.1     4656.1  -1.361  0.21047   
## Week_3        5126.2     6296.8   0.814  0.43915   
## Week_4         666.2     7141.2   0.093  0.92797   
## Week_5        3683.6     6272.4   0.587  0.57322   
## Week_6       -3942.2     4143.7  -0.951  0.36926   
## Week_7        2402.7     5507.5   0.436  0.67418   
## Week_8        -387.4     6655.4  -0.058  0.95501   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 51290 on 8 degrees of freedom
## Multiple R-squared:  0.897,  Adjusted R-squared:  0.215 
## F-statistic: 1.315 on 53 and 8 DF,  p-value: 0.3613

## [1] "Results for crop: Barley"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -8846.6 -1772.9   321.7  2013.5  5759.6 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 49738.42   12710.79   3.913  0.00446 **
## Week_9      -1003.30    1452.52  -0.691  0.50928   
## Week_10       124.56     791.36   0.157  0.87883   
## Week_11        35.82    1137.83   0.031  0.97566   
## Week_12       172.29     963.41   0.179  0.86251   
## Week_13     -1522.91    1548.72  -0.983  0.35424   
## Week_14      1770.90    1224.40   1.446  0.18610   
## Week_15       284.65    1081.86   0.263  0.79912   
## Week_16       607.79     935.02   0.650  0.53389   
## Week_17      -467.17    1370.55  -0.341  0.74199   
## Week_18      -178.92     879.98  -0.203  0.84396   
## Week_19      1051.84     640.36   1.643  0.13909   
## Week_20       506.47    1108.45   0.457  0.65988   
## Week_21        82.42     910.71   0.091  0.93011   
## Week_22       166.19     763.65   0.218  0.83317   
## Week_23      -435.58    1013.67  -0.430  0.67875   
## Week_24        16.29     901.62   0.018  0.98603   
## Week_25       -35.52     832.42  -0.043  0.96701   
## Week_26      -134.38     309.65  -0.434  0.67576   
## Week_27       876.91    1021.37   0.859  0.41556   
## Week_28      -324.57     741.53  -0.438  0.67318   
## Week_29       711.46    1332.92   0.534  0.60802   
## Week_30      -227.37     914.30  -0.249  0.80987   
## Week_31       213.79    1269.57   0.168  0.87045   
## Week_32      -120.85    1291.55  -0.094  0.92775   
## Week_33      -671.47    1356.26  -0.495  0.63385   
## Week_34      4398.79    2304.71   1.909  0.09273 . 
## Week_35     -1314.43    1479.22  -0.889  0.40015   
## Week_36        43.74    1507.23   0.029  0.97756   
## Week_37       505.93    1674.62   0.302  0.77027   
## Week_38       716.09    1343.30   0.533  0.60846   
## Week_39       -29.42    1249.02  -0.024  0.98179   
## Week_40        67.72    1225.28   0.055  0.95728   
## Week_41      -825.70    1413.48  -0.584  0.57521   
## Week_42       419.10    1731.45   0.242  0.81483   
## Week_43      -844.01    1599.50  -0.528  0.61204   
## Week_44       290.51     744.89   0.390  0.70671   
## Week_45     -1619.67    1558.91  -1.039  0.32920   
## Week_46      1131.17    1632.16   0.693  0.50789   
## Week_47     -1106.25     834.90  -1.325  0.22176   
## Week_48       546.27    1221.20   0.447  0.66651   
## Week_49       547.92     781.16   0.701  0.50294   
## Week_50       483.32     729.76   0.662  0.52639   
## Week_51      -710.68     691.74  -1.027  0.33430   
## Week_52      1171.78     823.23   1.423  0.19243   
## Week_53     -1221.48     742.86  -1.644  0.13873   
## Week_1        581.38     763.05   0.762  0.46797   
## Week_2      -1080.40     659.96  -1.637  0.14025   
## Week_3        599.55     892.51   0.672  0.52066   
## Week_4         28.50    1012.19   0.028  0.97823   
## Week_5        325.66     889.04   0.366  0.72364   
## Week_6       -226.46     587.33  -0.386  0.70986   
## Week_7       -335.21     780.63  -0.429  0.67896   
## Week_8        565.28     943.34   0.599  0.56560   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7269 on 8 degrees of freedom
## Multiple R-squared:  0.8218, Adjusted R-squared:  -0.3588 
## F-statistic: 0.6961 on 53 and 8 DF,  p-value: 0.7967

## [1] "Results for crop: Maize (corn)"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -14959.7  -4658.7    713.5   4478.2  14332.5 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 126972.73   29434.86   4.314  0.00257 **
## Week_9       -1557.14    3363.65  -0.463  0.65575   
## Week_10        224.15    1832.58   0.122  0.90567   
## Week_11        645.21    2634.91   0.245  0.81272   
## Week_12        -78.81    2231.00  -0.035  0.97269   
## Week_13      -3897.59    3586.43  -1.087  0.30880   
## Week_14       3446.49    2835.39   1.216  0.25882   
## Week_15        168.73    2505.30   0.067  0.94796   
## Week_16       1973.50    2165.25   0.911  0.38870   
## Week_17        625.86    3173.84   0.197  0.84860   
## Week_18       -904.07    2037.81  -0.444  0.66905   
## Week_19       2173.70    1482.90   1.466  0.18086   
## Week_20        804.46    2566.87   0.313  0.76199   
## Week_21         83.10    2108.96   0.039  0.96953   
## Week_22       -216.91    1768.42  -0.123  0.90540   
## Week_23       -399.86    2347.39  -0.170  0.86897   
## Week_24        900.39    2087.91   0.431  0.67768   
## Week_25      -2017.64    1927.67  -1.047  0.32584   
## Week_26        649.74     717.07   0.906  0.39135   
## Week_27       1327.77    2365.21   0.561  0.58992   
## Week_28        321.44    1717.18   0.187  0.85617   
## Week_29       2404.09    3086.70   0.779  0.45848   
## Week_30       -885.53    2117.27  -0.418  0.68677   
## Week_31       3093.34    2940.00   1.052  0.32347   
## Week_32      -2262.99    2990.89  -0.757  0.47096   
## Week_33       -558.41    3140.74  -0.178  0.86330   
## Week_34      13265.99    5337.10   2.486  0.03778 * 
## Week_35      -4490.64    3425.49  -1.311  0.22625   
## Week_36       2306.04    3490.35   0.661  0.52737   
## Week_37        129.02    3877.98   0.033  0.97427   
## Week_38        945.32    3110.73   0.304  0.76896   
## Week_39       -172.05    2892.40  -0.059  0.95403   
## Week_40      -2550.04    2837.43  -0.899  0.39505   
## Week_41      -1216.80    3273.26  -0.372  0.71974   
## Week_42         91.34    4009.58   0.023  0.98238   
## Week_43      -2321.82    3704.02  -0.627  0.54823   
## Week_44       1578.70    1724.96   0.915  0.38684   
## Week_45      -4516.59    3610.03  -1.251  0.24624   
## Week_46       3623.73    3779.64   0.959  0.36576   
## Week_47      -2075.97    1933.42  -1.074  0.31426   
## Week_48        209.10    2827.99   0.074  0.94288   
## Week_49       1561.89    1808.97   0.863  0.41305   
## Week_50       2020.28    1689.92   1.195  0.26613   
## Week_51      -2170.75    1601.88  -1.355  0.21240   
## Week_52       3126.18    1906.38   1.640  0.13967   
## Week_53      -3316.80    1720.26  -1.928  0.08999 . 
## Week_1        1061.06    1767.02   0.600  0.56481   
## Week_2       -2209.82    1528.29  -1.446  0.18620   
## Week_3        1858.65    2066.81   0.899  0.39476   
## Week_4        -663.32    2343.97  -0.283  0.78437   
## Week_5         921.87    2058.79   0.448  0.66619   
## Week_6        -824.92    1360.09  -0.607  0.56098   
## Week_7         741.25    1807.73   0.410  0.69253   
## Week_8        -444.14    2184.53  -0.203  0.84397   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 16830 on 8 degrees of freedom
## Multiple R-squared:  0.8859, Adjusted R-squared:  0.1301 
## F-statistic: 1.172 on 53 and 8 DF,  p-value: 0.4389

## [1] "Results for crop: Peaches and nectarines"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6128.6 -1875.2  -521.9  1580.5  9009.0 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 140722.54   16190.65   8.692 2.39e-05 ***
## Week_9        -997.16    1850.18  -0.539    0.605    
## Week_10       -438.30    1008.01  -0.435    0.675    
## Week_11        660.67    1449.33   0.456    0.661    
## Week_12        -86.30    1227.16  -0.070    0.946    
## Week_13       -385.25    1972.72  -0.195    0.850    
## Week_14        716.39    1559.61   0.459    0.658    
## Week_15       1132.62    1378.04   0.822    0.435    
## Week_16        419.10    1191.00   0.352    0.734    
## Week_17       -381.99    1745.77  -0.219    0.832    
## Week_18      -1140.56    1120.90  -1.018    0.339    
## Week_19        494.65     815.67   0.606    0.561    
## Week_20       1396.91    1411.91   0.989    0.351    
## Week_21        935.94    1160.03   0.807    0.443    
## Week_22       -364.02     972.72  -0.374    0.718    
## Week_23      -1277.51    1291.18  -0.989    0.351    
## Week_24        -33.15    1148.46  -0.029    0.978    
## Week_25        225.94    1060.31   0.213    0.837    
## Week_26       -650.62     394.42  -1.650    0.138    
## Week_27       1667.16    1300.99   1.281    0.236    
## Week_28       1037.54     944.54   1.098    0.304    
## Week_29       -185.89    1697.84  -0.109    0.916    
## Week_30       1064.37    1164.61   0.914    0.387    
## Week_31        491.13    1617.15   0.304    0.769    
## Week_32        418.15    1645.14   0.254    0.806    
## Week_33      -1907.56    1727.56  -1.104    0.302    
## Week_34       2609.20    2935.67   0.889    0.400    
## Week_35         72.42    1884.19   0.038    0.970    
## Week_36      -3211.51    1919.87  -1.673    0.133    
## Week_37        397.15    2133.08   0.186    0.857    
## Week_38        597.00    1711.06   0.349    0.736    
## Week_39        141.02    1590.96   0.089    0.932    
## Week_40        184.51    1560.73   0.118    0.909    
## Week_41        277.78    1800.46   0.154    0.881    
## Week_42       1547.83    2205.47   0.702    0.503    
## Week_43        675.11    2037.39   0.331    0.749    
## Week_44       -707.76     948.82  -0.746    0.477    
## Week_45        -96.43    1985.70  -0.049    0.962    
## Week_46       1919.05    2078.99   0.923    0.383    
## Week_47       -609.39    1063.48  -0.573    0.582    
## Week_48       1835.75    1555.53   1.180    0.272    
## Week_49       -862.92     995.02  -0.867    0.411    
## Week_50        661.96     929.54   0.712    0.497    
## Week_51        165.33     881.11   0.188    0.856    
## Week_52       -598.67    1048.61  -0.571    0.584    
## Week_53        196.79     946.23   0.208    0.840    
## Week_1         944.70     971.95   0.972    0.360    
## Week_2        -290.24     840.63  -0.345    0.739    
## Week_3         -49.87    1136.85  -0.044    0.966    
## Week_4         381.82    1289.30   0.296    0.775    
## Week_5        -143.96    1132.44  -0.127    0.902    
## Week_6        -552.49     748.12  -0.739    0.481    
## Week_7         317.66     994.34   0.319    0.758    
## Week_8         202.99    1201.60   0.169    0.870    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9259 on 8 degrees of freedom
## Multiple R-squared:  0.8753, Adjusted R-squared:  0.04915 
## F-statistic: 1.059 on 53 and 8 DF,  p-value: 0.5109

## [1] "Results for crop: Wheat"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6971.8 -1863.0     5.3  2000.5  4963.1 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 42556.40   12179.85   3.494  0.00815 **
## Week_9       -572.41    1391.85  -0.411  0.69168   
## Week_10       -24.19     758.30  -0.032  0.97533   
## Week_11      -198.47    1090.30  -0.182  0.86009   
## Week_12       -36.33     923.17  -0.039  0.96957   
## Week_13     -1125.27    1484.03  -0.758  0.47005   
## Week_14      1728.84    1173.26   1.474  0.17883   
## Week_15      -303.79    1036.67  -0.293  0.77695   
## Week_16       806.02     895.96   0.900  0.39459   
## Week_17      -910.06    1313.30  -0.693  0.50795   
## Week_18       134.93     843.22   0.160  0.87683   
## Week_19       848.20     613.61   1.382  0.20424   
## Week_20       275.93    1062.15   0.260  0.80159   
## Week_21       277.60     872.67   0.318  0.75855   
## Week_22       166.16     731.75   0.227  0.82606   
## Week_23      -665.94     971.32  -0.686  0.51234   
## Week_24        76.91     863.96   0.089  0.93125   
## Week_25      -250.94     797.65  -0.315  0.76111   
## Week_26        24.80     296.72   0.084  0.93544   
## Week_27       602.97     978.70   0.616  0.55496   
## Week_28      -312.19     710.55  -0.439  0.67203   
## Week_29       430.71    1277.25   0.337  0.74463   
## Week_30      -243.22     876.11  -0.278  0.78835   
## Week_31      1100.97    1216.54   0.905  0.39190   
## Week_32      -137.97    1237.60  -0.111  0.91398   
## Week_33      -412.52    1299.61  -0.317  0.75905   
## Week_34      4379.28    2208.44   1.983  0.08267 . 
## Week_35     -1474.46    1417.43  -1.040  0.32865   
## Week_36       315.70    1444.27   0.219  0.83244   
## Week_37       165.96    1604.67   0.103  0.92017   
## Week_38       442.82    1287.19   0.344  0.73970   
## Week_39       -72.83    1196.85  -0.061  0.95297   
## Week_40      -645.18    1174.10  -0.550  0.59766   
## Week_41      -332.59    1354.44  -0.246  0.81221   
## Week_42      1371.37    1659.12   0.827  0.43244   
## Week_43      -896.37    1532.68  -0.585  0.57478   
## Week_44       285.14     713.77   0.399  0.69999   
## Week_45     -1340.21    1493.80  -0.897  0.39582   
## Week_46      1491.12    1563.98   0.953  0.36830   
## Week_47      -869.81     800.03  -1.087  0.30861   
## Week_48       131.67    1170.19   0.113  0.91318   
## Week_49       483.78     748.53   0.646  0.53618   
## Week_50       392.91     699.27   0.562  0.58959   
## Week_51      -579.02     662.84  -0.874  0.40782   
## Week_52      1104.11     788.84   1.400  0.19918   
## Week_53     -1153.56     711.83  -1.621  0.14377   
## Week_1        562.22     731.18   0.769  0.46404   
## Week_2       -824.90     632.39  -1.304  0.22837   
## Week_3        552.57     855.23   0.646  0.53630   
## Week_4        -69.44     969.91  -0.072  0.94468   
## Week_5        155.36     851.91   0.182  0.85983   
## Week_6       -120.42     562.79  -0.214  0.83593   
## Week_7       -471.93     748.02  -0.631  0.54570   
## Week_8        539.20     903.94   0.597  0.56733   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6966 on 8 degrees of freedom
## Multiple R-squared:  0.8461, Adjusted R-squared:  -0.1734 
## F-statistic: 0.8299 on 53 and 8 DF,  p-value: 0.6859

## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4605.6 -1360.4  -232.6  1449.1  5309.5 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 38521.875  11000.536   3.502  0.00806 **
## Week_9        647.846   1257.080   0.515  0.62024   
## Week_10      -899.902    684.880  -1.314  0.22529   
## Week_11      -182.973    984.729  -0.186  0.85722   
## Week_12     -1017.470    833.780  -1.220  0.25709   
## Week_13      1162.969   1340.338   0.868  0.41085   
## Week_14       691.952   1059.656   0.653  0.53207   
## Week_15      -362.174    936.293  -0.387  0.70898   
## Week_16       718.834    809.209   0.888  0.40029   
## Week_17      -857.703   1186.143  -0.723  0.49021   
## Week_18      -396.117    761.579  -0.520  0.61706   
## Week_19      -157.993    554.196  -0.285  0.78282   
## Week_20       555.261    959.304   0.579  0.57864   
## Week_21       449.034    788.171   0.570  0.58451   
## Week_22      -714.463    660.901  -1.081  0.31119   
## Week_23       -66.390    877.276  -0.076  0.94153   
## Week_24      -176.164    780.305  -0.226  0.82705   
## Week_25      -375.197    720.417  -0.521  0.61661   
## Week_26       134.113    267.986   0.500  0.63024   
## Week_27       172.668    883.939   0.195  0.85000   
## Week_28       132.205    641.753   0.206  0.84193   
## Week_29      -903.094   1153.577  -0.783  0.45625   
## Week_30      -271.810    791.277  -0.344  0.74007   
## Week_31      2488.802   1098.750   2.265  0.05329 . 
## Week_32       849.156   1117.768   0.760  0.46923   
## Week_33      -150.918   1173.771  -0.129  0.90087   
## Week_34       988.691   1994.606   0.496  0.63345   
## Week_35       937.116   1280.191   0.732  0.48505   
## Week_36     -1666.638   1304.430  -1.278  0.23719   
## Week_37      -581.257   1449.298  -0.401  0.69887   
## Week_38      -251.693   1162.559  -0.216  0.83402   
## Week_39     -1814.209   1080.961  -1.678  0.13180   
## Week_40      -133.617   1060.418  -0.126  0.90284   
## Week_41       867.682   1223.298   0.709  0.49829   
## Week_42      2195.974   1498.479   1.465  0.18096   
## Week_43      -267.878   1384.282  -0.194  0.85138   
## Week_44       704.986    644.661   1.094  0.30597   
## Week_45      -269.031   1349.159  -0.199  0.84692   
## Week_46       743.144   1412.546   0.526  0.61309   
## Week_47       923.095    722.565   1.278  0.23724   
## Week_48      -495.570   1056.889  -0.469  0.65166   
## Week_49      -154.610    676.057  -0.229  0.82484   
## Week_50         4.261    631.567   0.007  0.99478   
## Week_51        77.288    598.662   0.129  0.90046   
## Week_52       -88.032    712.463  -0.124  0.90471   
## Week_53       105.084    642.904   0.163  0.87422   
## Week_1        343.148    660.381   0.520  0.61739   
## Week_2        248.877    571.158   0.436  0.67454   
## Week_3       -237.961    772.420  -0.308  0.76590   
## Week_4        -83.401    875.999  -0.095  0.92649   
## Week_5       -691.893    769.421  -0.899  0.39479   
## Week_6        434.596    508.300   0.855  0.41742   
## Week_7       -469.406    675.593  -0.695  0.50685   
## Week_8        275.511    816.413   0.337  0.74445   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6291 on 8 degrees of freedom
## Multiple R-squared:  0.8683, Adjusted R-squared:  -0.00406 
## F-statistic: 0.9953 on 53 and 8 DF,  p-value: 0.5563

## [1] "Results for crop: Grapes"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -17114.2  -2924.9   -158.6   3303.6  11983.9 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 102045.2    24321.9   4.196  0.00301 **
## Week_9       -2951.6     2779.4  -1.062  0.31926   
## Week_10        504.3     1514.3   0.333  0.74765   
## Week_11       -461.8     2177.2  -0.212  0.83732   
## Week_12       1608.8     1843.5   0.873  0.40826   
## Week_13      -5174.7     2963.5  -1.746  0.11893   
## Week_14       4605.0     2342.9   1.966  0.08493 . 
## Week_15       1154.6     2070.1   0.558  0.59229   
## Week_16       1984.7     1789.1   1.109  0.29953   
## Week_17      -3014.6     2622.5  -1.150  0.28355   
## Week_18       1603.1     1683.8   0.952  0.36893   
## Week_19       3047.2     1225.3   2.487  0.03771 * 
## Week_20        450.6     2121.0   0.212  0.83706   
## Week_21      -1308.3     1742.6  -0.751  0.47430   
## Week_22       -180.5     1461.2  -0.124  0.90473   
## Week_23      -1035.6     1939.6  -0.534  0.60792   
## Week_24       1411.0     1725.2   0.818  0.43711   
## Week_25      -1109.2     1592.8  -0.696  0.50591   
## Week_26        111.4      592.5   0.188  0.85557   
## Week_27        853.8     1954.4   0.437  0.67377   
## Week_28        400.7     1418.9   0.282  0.78479   
## Week_29       5697.1     2550.5   2.234  0.05597 . 
## Week_30      -3374.8     1749.5  -1.929  0.08986 . 
## Week_31      -1310.3     2429.3  -0.539  0.60432   
## Week_32        180.1     2471.4   0.073  0.94369   
## Week_33      -2430.6     2595.2  -0.937  0.37639   
## Week_34       9341.6     4410.0   2.118  0.06701 . 
## Week_35       -629.7     2830.5  -0.222  0.82951   
## Week_36       1093.0     2884.1   0.379  0.71457   
## Week_37        526.9     3204.4   0.164  0.87347   
## Week_38       2352.0     2570.4   0.915  0.38692   
## Week_39        305.2     2390.0   0.128  0.90154   
## Week_40      -2235.2     2344.6  -0.953  0.36832   
## Week_41      -1094.2     2704.7  -0.405  0.69641   
## Week_42       -940.5     3313.1  -0.284  0.78373   
## Week_43      -2704.7     3060.6  -0.884  0.40264   
## Week_44       1785.3     1425.3   1.253  0.24575   
## Week_45      -5830.9     2983.0  -1.955  0.08636 . 
## Week_46       3775.0     3123.1   1.209  0.26128   
## Week_47      -2768.8     1597.6  -1.733  0.12131   
## Week_48       3077.7     2336.8   1.317  0.22428   
## Week_49       1504.0     1494.7   1.006  0.34378   
## Week_50       1636.8     1396.4   1.172  0.27484   
## Week_51      -2625.6     1323.6  -1.984  0.08258 . 
## Week_52       4619.1     1575.2   2.932  0.01893 * 
## Week_53      -4981.3     1421.4  -3.504  0.00803 **
## Week_1        1332.3     1460.1   0.912  0.38819   
## Week_2       -3469.2     1262.8  -2.747  0.02517 * 
## Week_3         570.3     1707.8   0.334  0.74701   
## Week_4        1625.0     1936.8   0.839  0.42582   
## Week_5         584.1     1701.2   0.343  0.74017   
## Week_6        -945.8     1123.8  -0.842  0.42448   
## Week_7         162.2     1493.7   0.109  0.91622   
## Week_8         483.5     1805.1   0.268  0.79558   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 13910 on 8 degrees of freedom
## Multiple R-squared:  0.9061, Adjusted R-squared:  0.2844 
## F-statistic: 1.457 on 53 and 8 DF,  p-value: 0.2983

## [1] "Results for crop: Raspberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -7868.6 -2352.5  -172.8  2045.0 10330.6 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 69498.34   17385.83   3.997  0.00396 **
## Week_9        182.82    1986.76   0.092  0.92894   
## Week_10      -488.24    1082.42  -0.451  0.66392   
## Week_11      1401.70    1556.32   0.901  0.39408   
## Week_12       262.02    1317.75   0.199  0.84735   
## Week_13     -3316.72    2118.34  -1.566  0.15605   
## Week_14       778.70    1674.74   0.465  0.65435   
## Week_15      1359.81    1479.77   0.919  0.38500   
## Week_16      -271.98    1278.92  -0.213  0.83691   
## Week_17      1749.22    1874.64   0.933  0.37807   
## Week_18      -199.49    1203.64  -0.166  0.87247   
## Week_19      1593.09     875.88   1.819  0.10644   
## Week_20      -580.99    1516.14  -0.383  0.71155   
## Week_21     -1201.80    1245.67  -0.965  0.36291   
## Week_22      1499.66    1044.52   1.436  0.18900   
## Week_23      1536.80    1386.49   1.108  0.29989   
## Week_24       -97.31    1233.24  -0.079  0.93905   
## Week_25      -431.56    1138.59  -0.379  0.71453   
## Week_26        45.93     423.54   0.108  0.91631   
## Week_27       354.47    1397.02   0.254  0.80610   
## Week_28       384.90    1014.26   0.379  0.71420   
## Week_29      1914.92    1823.17   1.050  0.32426   
## Week_30      -175.08    1250.58  -0.140  0.89212   
## Week_31     -2642.47    1736.52  -1.522  0.16658   
## Week_32     -2659.94    1766.58  -1.506  0.17056   
## Week_33      -355.73    1855.09  -0.192  0.85271   
## Week_34      5987.94    3152.38   1.899  0.09404 . 
## Week_35     -5116.09    2023.28  -2.529  0.03533 * 
## Week_36      3647.65    2061.59   1.769  0.11480   
## Week_37      1307.99    2290.55   0.571  0.58365   
## Week_38      1542.16    1837.37   0.839  0.42565   
## Week_39       -30.27    1708.41  -0.018  0.98630   
## Week_40      -550.55    1675.94  -0.329  0.75097   
## Week_41      1229.82    1933.37   0.636  0.54248   
## Week_42     -3571.84    2368.28  -1.508  0.16993   
## Week_43      1992.44    2187.79   0.911  0.38906   
## Week_44       484.27    1018.86   0.475  0.64728   
## Week_45     -3217.75    2132.28  -1.509  0.16972   
## Week_46      1761.63    2232.46   0.789  0.45280   
## Week_47      -259.76    1141.98  -0.227  0.82577   
## Week_48      -250.87    1670.36  -0.150  0.88433   
## Week_49      1060.20    1068.48   0.992  0.35013   
## Week_50      -280.36     998.16  -0.281  0.78593   
## Week_51      -999.67     946.16  -1.057  0.32157   
## Week_52       970.72    1126.01   0.862  0.41373   
## Week_53     -2040.22    1016.08  -2.008  0.07953 . 
## Week_1        -87.28    1043.70  -0.084  0.93541   
## Week_2       -991.48     902.69  -1.098  0.30400   
## Week_3        288.08    1220.77   0.236  0.81938   
## Week_4        577.44    1384.47   0.417  0.68759   
## Week_5        501.33    1216.03   0.412  0.69097   
## Week_6       -537.45     803.34  -0.669  0.52232   
## Week_7        888.25    1067.74   0.832  0.42960   
## Week_8       -962.18    1290.30  -0.746  0.47719   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9943 on 8 degrees of freedom
## Multiple R-squared:  0.8581, Adjusted R-squared:  -0.08233 
## F-statistic: 0.9124 on 53 and 8 DF,  p-value: 0.6193

## [1] "Results for crop: Strawberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -23747.8  -3986.8   -445.8   4411.7  16525.0 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 125748.66   34010.38   3.697  0.00607 **
## Week_9       -1592.65    3886.52  -0.410  0.69272   
## Week_10       -219.32    2117.45  -0.104  0.92005   
## Week_11        -20.33    3044.49  -0.007  0.99483   
## Week_12       -342.96    2577.80  -0.133  0.89744   
## Week_13      -2675.32    4143.93  -0.646  0.53661   
## Week_14       2763.37    3276.14   0.843  0.42346   
## Week_15        694.49    2894.74   0.240  0.81643   
## Week_16       3147.38    2501.83   1.258  0.24386   
## Week_17      -1113.40    3667.20  -0.304  0.76917   
## Week_18       -571.19    2354.58  -0.243  0.81443   
## Week_19       2977.61    1713.41   1.738  0.12044   
## Week_20       2108.39    2965.88   0.711  0.49736   
## Week_21       -293.62    2436.79  -0.120  0.90706   
## Week_22        203.26    2043.31   0.099  0.92321   
## Week_23      -1714.36    2712.28  -0.632  0.54497   
## Week_24        818.08    2412.47   0.339  0.74326   
## Week_25      -1431.45    2227.32  -0.643  0.53841   
## Week_26        118.06     828.53   0.142  0.89022   
## Week_27       2046.98    2732.88   0.749  0.47529   
## Week_28       1387.02    1984.11   0.699  0.50432   
## Week_29       2312.19    3566.52   0.648  0.53495   
## Week_30      -2410.47    2446.39  -0.985  0.35333   
## Week_31       3770.53    3397.01   1.110  0.29926   
## Week_32       -770.19    3455.81  -0.223  0.82922   
## Week_33      -3133.37    3628.95  -0.863  0.41303   
## Week_34      14017.70    6166.73   2.273  0.05263 . 
## Week_35      -1243.10    3957.97  -0.314  0.76150   
## Week_36       -611.38    4032.91  -0.152  0.88326   
## Week_37         49.40    4480.80   0.011  0.99147   
## Week_38       1304.50    3594.29   0.363  0.72605   
## Week_39       -527.39    3342.01  -0.158  0.87852   
## Week_40      -1724.85    3278.50  -0.526  0.61308   
## Week_41       -436.42    3782.07  -0.115  0.91098   
## Week_42       1175.70    4632.85   0.254  0.80607   
## Week_43      -2445.12    4279.79  -0.571  0.58347   
## Week_44       1570.02    1993.10   0.788  0.45356   
## Week_45      -6939.13    4171.20  -1.664  0.13477   
## Week_46       4884.34    4367.17   1.118  0.29584   
## Week_47      -1848.76    2233.96  -0.828  0.43190   
## Week_48       2050.01    3267.59   0.627  0.54790   
## Week_49       1332.17    2090.17   0.637  0.54170   
## Week_50       1563.30    1952.62   0.801  0.44648   
## Week_51      -1799.93    1850.89  -0.972  0.35930   
## Week_52       3067.83    2202.72   1.393  0.20118   
## Week_53      -3768.44    1987.67  -1.896  0.09456 . 
## Week_1        1766.26    2041.70   0.865  0.41218   
## Week_2       -2662.03    1765.85  -1.508  0.17011   
## Week_3        1234.90    2388.09   0.517  0.61907   
## Week_4         420.36    2708.33   0.155  0.88050   
## Week_5         794.93    2378.82   0.334  0.74684   
## Week_6       -1354.51    1571.51  -0.862  0.41382   
## Week_7        1016.64    2088.73   0.487  0.63951   
## Week_8        -737.96    2524.11  -0.292  0.77745   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 19450 on 8 degrees of freedom
## Multiple R-squared:  0.8715, Adjusted R-squared:  0.02028 
## F-statistic: 1.024 on 53 and 8 DF,  p-value: 0.5357

linear reg for yield VS daily Max Temp

Abbotsford

## [1] "There are 43  NA in the matrix X in Abbotsford station"
## [1] "Results for crop: Apples"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -33286 -15871     64  10493  55755 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -515639.03  318913.35  -1.617   0.1446  
## Week_9        -2699.29    7229.07  -0.373   0.7186  
## Week_10         662.86    8539.36   0.078   0.9400  
## Week_11       -3283.03   11892.83  -0.276   0.7895  
## Week_12       13682.96    8156.72   1.678   0.1320  
## Week_13       -5296.41   13256.23  -0.400   0.6999  
## Week_14      -21007.50   14738.51  -1.425   0.1919  
## Week_15       24685.72   11893.14   2.076   0.0716 .
## Week_16         422.03   15611.57   0.027   0.9791  
## Week_17        3438.96   14641.66   0.235   0.8202  
## Week_18        4679.78   14121.61   0.331   0.7489  
## Week_19        6239.70    9835.83   0.634   0.5435  
## Week_20         970.91    9538.08   0.102   0.9214  
## Week_21       -3476.16   13061.20  -0.266   0.7969  
## Week_22        -561.02    8409.07  -0.067   0.9484  
## Week_23       -1811.93    7715.60  -0.235   0.8202  
## Week_24       -7583.53    8482.87  -0.894   0.3974  
## Week_25       -2228.60    8464.18  -0.263   0.7990  
## Week_26        9461.88    8506.32   1.112   0.2983  
## Week_27        -127.81   16180.24  -0.008   0.9939  
## Week_28        6607.71   12773.95   0.517   0.6190  
## Week_29       -5452.17    9746.05  -0.559   0.5912  
## Week_30       -6857.25   13072.68  -0.525   0.6141  
## Week_31        8895.00   10793.52   0.824   0.4338  
## Week_32       -3482.08    7606.78  -0.458   0.6593  
## Week_33       -4081.18    7804.30  -0.523   0.6152  
## Week_34       25782.50   13272.42   1.943   0.0880 .
## Week_35         755.61    8072.85   0.094   0.9277  
## Week_36       -4451.57    8823.46  -0.505   0.6275  
## Week_37       16769.26   10828.19   1.549   0.1601  
## Week_38        3286.65   10453.60   0.314   0.7613  
## Week_39       -6308.72   14854.03  -0.425   0.6822  
## Week_40       -1882.00   10391.28  -0.181   0.8608  
## Week_41       -4544.04    9701.09  -0.468   0.6520  
## Week_42        6939.20    9662.43   0.718   0.4931  
## Week_43        4836.54    8955.88   0.540   0.6039  
## Week_44       -2847.69    6360.79  -0.448   0.6662  
## Week_45       -4224.03   17600.02  -0.240   0.8164  
## Week_46        4033.82    8835.63   0.457   0.6601  
## Week_47        1498.37    4771.24   0.314   0.7615  
## Week_48       -5214.67    6060.88  -0.860   0.4146  
## Week_49       -6406.70    4160.01  -1.540   0.1621  
## Week_50        1345.64    4146.94   0.324   0.7539  
## Week_51       -2945.47    4849.56  -0.607   0.5604  
## Week_52         166.99    6111.42   0.027   0.9789  
## Week_53       -1468.17    4055.60  -0.362   0.7267  
## Week_1         2439.59    4661.41   0.523   0.6149  
## Week_2           79.32    5724.38   0.014   0.9893  
## Week_3         1439.15    5142.70   0.280   0.7867  
## Week_4        -5114.54    7575.27  -0.675   0.5186  
## Week_5         5698.22    4722.91   1.207   0.2621  
## Week_6        -1247.71    5701.82  -0.219   0.8323  
## Week_7         4085.42    7141.98   0.572   0.5830  
## Week_8        -8259.82    8060.96  -1.025   0.3355  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 53080 on 8 degrees of freedom
## Multiple R-squared:  0.8897, Adjusted R-squared:  0.1591 
## F-statistic: 1.218 on 53 and 8 DF,  p-value: 0.4124

## [1] "Results for crop: Barley"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5352.9 -1289.6    44.5  1268.6  5186.5 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -44334.966  38559.454  -1.150   0.2834  
## Week_9          58.714    874.059   0.067   0.9481  
## Week_10       -759.866   1032.484  -0.736   0.4828  
## Week_11       -815.310   1437.949  -0.567   0.5863  
## Week_12       1782.095    986.220   1.807   0.1084  
## Week_13       -547.485   1602.796  -0.342   0.7415  
## Week_14      -1814.796   1782.017  -1.018   0.3383  
## Week_15       3325.647   1437.986   2.313   0.0495 *
## Week_16        150.761   1887.577   0.080   0.9383  
## Week_17        906.197   1770.306   0.512   0.6226  
## Week_18       1059.011   1707.428   0.620   0.5524  
## Week_19       1135.631   1189.239   0.955   0.3676  
## Week_20        177.984   1153.238   0.154   0.8812  
## Week_21       -753.745   1579.215  -0.477   0.6459  
## Week_22        444.207   1016.731   0.437   0.6737  
## Week_23       -180.859    932.885  -0.194   0.8511  
## Week_24       -847.220   1025.654  -0.826   0.4327  
## Week_25       -882.623   1023.394  -0.862   0.4135  
## Week_26       1021.212   1028.489   0.993   0.3498  
## Week_27        318.716   1956.334   0.163   0.8746  
## Week_28        -22.215   1544.484  -0.014   0.9889  
## Week_29       -979.989   1178.383  -0.832   0.4297  
## Week_30       -906.367   1580.603  -0.573   0.5821  
## Week_31        696.928   1305.032   0.534   0.6078  
## Week_32        402.604    919.727   0.438   0.6732  
## Week_33       -327.092    943.609  -0.347   0.7378  
## Week_34       2819.259   1604.753   1.757   0.1170  
## Week_35         96.135    976.079   0.098   0.9240  
## Week_36       -610.709   1066.834  -0.572   0.5827  
## Week_37        900.280   1309.224   0.688   0.5111  
## Week_38       1341.980   1263.933   1.062   0.3193  
## Week_39      -1029.434   1795.984  -0.573   0.5823  
## Week_40       -166.678   1256.398  -0.133   0.8977  
## Week_41       -359.797   1172.948  -0.307   0.7669  
## Week_42        257.680   1168.274   0.221   0.8310  
## Week_43        173.944   1082.845   0.161   0.8764  
## Week_44          4.258    769.076   0.006   0.9957  
## Week_45      -1522.658   2127.999  -0.716   0.4946  
## Week_46        892.782   1068.306   0.836   0.4276  
## Week_47          6.421    576.885   0.011   0.9914  
## Week_48       -920.724    732.814  -1.256   0.2444  
## Week_49       -820.255    502.982  -1.631   0.1416  
## Week_50        368.577    501.402   0.735   0.4833  
## Week_51       -264.215    586.355  -0.451   0.6642  
## Week_52         22.269    738.925   0.030   0.9767  
## Week_53       -234.739    490.358  -0.479   0.6450  
## Week_1        -169.375    563.606  -0.301   0.7714  
## Week_2         217.385    692.128   0.314   0.7615  
## Week_3        -101.773    621.798  -0.164   0.8740  
## Week_4        -244.491    915.918  -0.267   0.7963  
## Week_5         233.264    571.042   0.408   0.6936  
## Week_6         138.802    689.400   0.201   0.8455  
## Week_7         445.329    863.529   0.516   0.6200  
## Week_8        -753.527    974.642  -0.773   0.4617  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6418 on 8 degrees of freedom
## Multiple R-squared:  0.8611, Adjusted R-squared:  -0.05905 
## F-statistic: 0.9358 on 53 and 8 DF,  p-value: 0.601

## [1] "Results for crop: Maize (corn)"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -13144.2  -3118.6    213.3   2357.2  20766.9 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -1.658e+05  9.228e+04  -1.797   0.1101  
## Week_9       4.155e+01  2.092e+03   0.020   0.9846  
## Week_10      2.752e+02  2.471e+03   0.111   0.9141  
## Week_11     -2.697e+03  3.441e+03  -0.784   0.4557  
## Week_12      3.838e+03  2.360e+03   1.626   0.1426  
## Week_13      1.581e+03  3.836e+03   0.412   0.6910  
## Week_14     -6.251e+03  4.265e+03  -1.466   0.1809  
## Week_15      5.032e+03  3.441e+03   1.462   0.1818  
## Week_16     -1.823e+03  4.517e+03  -0.404   0.6971  
## Week_17     -3.512e+02  4.237e+03  -0.083   0.9360  
## Week_18      1.651e+03  4.086e+03   0.404   0.6968  
## Week_19      1.208e+03  2.846e+03   0.424   0.6825  
## Week_20     -3.434e+02  2.760e+03  -0.124   0.9040  
## Week_21     -2.656e+02  3.779e+03  -0.070   0.9457  
## Week_22     -8.675e+00  2.433e+03  -0.004   0.9972  
## Week_23     -5.947e+02  2.232e+03  -0.266   0.7967  
## Week_24     -1.048e+03  2.454e+03  -0.427   0.6805  
## Week_25     -3.904e+03  2.449e+03  -1.594   0.1496  
## Week_26      4.639e+03  2.461e+03   1.885   0.0962 .
## Week_27     -7.126e+02  4.682e+03  -0.152   0.8828  
## Week_28      4.893e+03  3.696e+03   1.324   0.2221  
## Week_29     -8.304e+02  2.820e+03  -0.294   0.7759  
## Week_30      1.064e+03  3.783e+03   0.281   0.7857  
## Week_31      2.133e+03  3.123e+03   0.683   0.5139  
## Week_32     -3.295e+02  2.201e+03  -0.150   0.8847  
## Week_33     -3.800e+02  2.258e+03  -0.168   0.8705  
## Week_34      5.948e+03  3.840e+03   1.549   0.1600  
## Week_35     -1.161e+03  2.336e+03  -0.497   0.6324  
## Week_36     -1.597e+01  2.553e+03  -0.006   0.9952  
## Week_37      1.222e+03  3.133e+03   0.390   0.7066  
## Week_38      1.341e+03  3.025e+03   0.443   0.6692  
## Week_39     -1.100e+03  4.298e+03  -0.256   0.8045  
## Week_40     -1.921e+03  3.007e+03  -0.639   0.5407  
## Week_41      8.341e+02  2.807e+03   0.297   0.7739  
## Week_42      9.599e+02  2.796e+03   0.343   0.7402  
## Week_43     -4.337e+02  2.591e+03  -0.167   0.8712  
## Week_44      1.356e+03  1.840e+03   0.737   0.4823  
## Week_45      1.917e+02  5.092e+03   0.038   0.9709  
## Week_46      2.785e+03  2.557e+03   1.089   0.3077  
## Week_47     -3.577e+02  1.381e+03  -0.259   0.8021  
## Week_48     -5.095e+02  1.754e+03  -0.291   0.7788  
## Week_49     -2.460e+03  1.204e+03  -2.044   0.0752 .
## Week_50      6.180e+02  1.200e+03   0.515   0.6204  
## Week_51     -3.299e+02  1.403e+03  -0.235   0.8201  
## Week_52     -3.944e+01  1.768e+03  -0.022   0.9828  
## Week_53     -3.528e+02  1.173e+03  -0.301   0.7713  
## Week_1      -4.198e+02  1.349e+03  -0.311   0.7636  
## Week_2      -3.267e+02  1.656e+03  -0.197   0.8486  
## Week_3       5.732e+01  1.488e+03   0.039   0.9702  
## Week_4       1.699e+02  2.192e+03   0.077   0.9401  
## Week_5       5.371e+02  1.367e+03   0.393   0.7046  
## Week_6      -5.423e+02  1.650e+03  -0.329   0.7508  
## Week_7       5.621e+02  2.067e+03   0.272   0.7925  
## Week_8      -2.140e+03  2.332e+03  -0.917   0.3857  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15360 on 8 degrees of freedom
## Multiple R-squared:  0.905,  Adjusted R-squared:  0.2759 
## F-statistic: 1.439 on 53 and 8 DF,  p-value: 0.3059

## [1] "Results for crop: Peaches and nectarines"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4328.4 -1282.9  -292.3  1570.1  5701.7 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -41717.07   39041.72  -1.069   0.3165  
## Week_9         839.19     884.99   0.948   0.3708  
## Week_10       -397.20    1045.40  -0.380   0.7139  
## Week_11       1193.88    1455.93   0.820   0.4360  
## Week_12       1023.88     998.55   1.025   0.3352  
## Week_13       1285.67    1622.84   0.792   0.4511  
## Week_14       -787.98    1804.30  -0.437   0.6739  
## Week_15        938.36    1455.97   0.644   0.5373  
## Week_16      -4010.89    1911.18  -2.099   0.0691 .
## Week_17      -1044.38    1792.45  -0.583   0.5762  
## Week_18      -3451.28    1728.78  -1.996   0.0810 .
## Week_19       1451.55    1204.11   1.205   0.2625  
## Week_20        562.63    1167.66   0.482   0.6428  
## Week_21       1832.38    1598.97   1.146   0.2849  
## Week_22        482.47    1029.45   0.469   0.6518  
## Week_23       1626.79     944.55   1.722   0.1233  
## Week_24      -1942.25    1038.48  -1.870   0.0984 .
## Week_25       -310.18    1036.19  -0.299   0.7723  
## Week_26        477.32    1041.35   0.458   0.6589  
## Week_27      -2770.72    1980.80  -1.399   0.1994  
## Week_28       3908.15    1563.80   2.499   0.0370 *
## Week_29       -470.22    1193.12  -0.394   0.7038  
## Week_30       2359.89    1600.37   1.475   0.1786  
## Week_31       2777.64    1321.35   2.102   0.0687 .
## Week_32         44.05     931.23   0.047   0.9634  
## Week_33      -1857.94     955.41  -1.945   0.0877 .
## Week_34       1058.34    1624.82   0.651   0.5331  
## Week_35       -106.27     988.29  -0.108   0.9170  
## Week_36      -2370.10    1080.18  -2.194   0.0595 .
## Week_37         92.01    1325.60   0.069   0.9464  
## Week_38       1403.39    1279.74   1.097   0.3047  
## Week_39       1582.06    1818.45   0.870   0.4096  
## Week_40       -527.00    1272.11  -0.414   0.6896  
## Week_41       1292.02    1187.62   1.088   0.3083  
## Week_42        439.40    1182.89   0.371   0.7199  
## Week_43       1739.76    1096.39   1.587   0.1512  
## Week_44       -797.62     778.69  -1.024   0.3357  
## Week_45       3203.05    2154.61   1.487   0.1754  
## Week_46       2858.50    1081.67   2.643   0.0296 *
## Week_47       -616.14     584.10  -1.055   0.3223  
## Week_48        473.59     741.98   0.638   0.5411  
## Week_49       -893.53     509.27  -1.755   0.1174  
## Week_50        839.97     507.67   1.655   0.1366  
## Week_51       -122.51     593.69  -0.206   0.8417  
## Week_52       -225.77     748.17  -0.302   0.7705  
## Week_53        321.44     496.49   0.647   0.5355  
## Week_1        -327.33     570.65  -0.574   0.5820  
## Week_2        -923.15     700.78  -1.317   0.2242  
## Week_3         216.77     629.57   0.344   0.7395  
## Week_4         702.83     927.37   0.758   0.4703  
## Week_5        -233.35     578.18  -0.404   0.6971  
## Week_6        -748.88     698.02  -1.073   0.3146  
## Week_7       -1822.14     874.33  -2.084   0.0707 .
## Week_8          34.31     986.83   0.035   0.9731  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6498 on 8 degrees of freedom
## Multiple R-squared:  0.9386, Adjusted R-squared:  0.5317 
## F-statistic: 2.307 on 53 and 8 DF,  p-value: 0.1044

## [1] "Results for crop: Wheat"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4802.0 -1403.6   199.2  1119.6  6319.7 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -50474.52   37299.47  -1.353    0.213  
## Week_9         192.63     845.50   0.228    0.825  
## Week_10       -822.69     998.75  -0.824    0.434  
## Week_11      -1955.05    1390.96  -1.406    0.197  
## Week_12       1578.64     953.99   1.655    0.137  
## Week_13        938.10    1550.42   0.605    0.562  
## Week_14      -2395.75    1723.79  -1.390    0.202  
## Week_15       2907.22    1391.00   2.090    0.070 .
## Week_16       -342.31    1825.90  -0.187    0.856  
## Week_17       1313.88    1712.46   0.767    0.465  
## Week_18       2118.79    1651.64   1.283    0.235  
## Week_19        470.54    1150.38   0.409    0.693  
## Week_20        265.12    1115.55   0.238    0.818  
## Week_21       -863.21    1527.61  -0.565    0.588  
## Week_22        -20.41     983.51  -0.021    0.984  
## Week_23       -302.03     902.40  -0.335    0.746  
## Week_24       -963.76     992.14  -0.971    0.360  
## Week_25      -1082.20     989.95  -1.093    0.306  
## Week_26        823.11     994.88   0.827    0.432  
## Week_27       1124.09    1892.41   0.594    0.569  
## Week_28        102.34    1494.02   0.069    0.947  
## Week_29      -1314.56    1139.88  -1.153    0.282  
## Week_30       -704.89    1528.95  -0.461    0.657  
## Week_31       1106.09    1262.39   0.876    0.406  
## Week_32        175.23     889.67   0.197    0.849  
## Week_33       -429.60     912.78  -0.471    0.650  
## Week_34       2775.00    1552.32   1.788    0.112  
## Week_35        188.63     944.18   0.200    0.847  
## Week_36       -498.40    1031.97  -0.483    0.642  
## Week_37        532.91    1266.44   0.421    0.685  
## Week_38       1130.34    1222.63   0.925    0.382  
## Week_39      -1585.68    1737.30  -0.913    0.388  
## Week_40       -197.41    1215.34  -0.162    0.875  
## Week_41        340.66    1134.62   0.300    0.772  
## Week_42        891.02    1130.10   0.788    0.453  
## Week_43        672.88    1047.46   0.642    0.539  
## Week_44         24.17     743.95   0.032    0.975  
## Week_45      -1452.64    2058.46  -0.706    0.500  
## Week_46       1574.93    1033.40   1.524    0.166  
## Week_47       -216.39     558.03  -0.388    0.708  
## Week_48       -561.95     708.87  -0.793    0.451  
## Week_49       -790.99     486.55  -1.626    0.143  
## Week_50        103.46     485.02   0.213    0.836  
## Week_51       -301.43     567.19  -0.531    0.610  
## Week_52        -11.83     714.78  -0.017    0.987  
## Week_53       -277.62     474.33  -0.585    0.574  
## Week_1          48.25     545.19   0.088    0.932  
## Week_2         388.26     669.51   0.580    0.578  
## Week_3        -475.50     601.48  -0.791    0.452  
## Week_4        -354.52     885.99  -0.400    0.700  
## Week_5         321.76     552.38   0.582    0.576  
## Week_6        -197.01     666.87  -0.295    0.775  
## Week_7         448.14     835.31   0.536    0.606  
## Week_8        -958.74     942.79  -1.017    0.339  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6208 on 8 degrees of freedom
## Multiple R-squared:  0.8778, Adjusted R-squared:  0.06796 
## F-statistic: 1.084 on 53 and 8 DF,  p-value: 0.4944

## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5702.7 -1349.4     1.4  1669.4  3881.0 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)  
## (Intercept)  7839.85   36258.18   0.216   0.8342  
## Week_9       -333.67     821.89  -0.406   0.6954  
## Week_10     -1178.51     970.86  -1.214   0.2594  
## Week_11     -3590.01    1352.13  -2.655   0.0290 *
## Week_12      1261.74     927.36   1.361   0.2107  
## Week_13      2169.08    1507.14   1.439   0.1880  
## Week_14      -555.95    1675.66  -0.332   0.7486  
## Week_15       535.20    1352.17   0.396   0.7026  
## Week_16       960.16    1774.92   0.541   0.6033  
## Week_17      2228.02    1664.65   1.338   0.2175  
## Week_18      2199.17    1605.53   1.370   0.2080  
## Week_19      -325.64    1118.26  -0.291   0.7783  
## Week_20       844.90    1084.41   0.779   0.4583  
## Week_21      -889.37    1484.97  -0.599   0.5658  
## Week_22     -1917.14     956.05  -2.005   0.0799 .
## Week_23      -226.05     877.21  -0.258   0.8031  
## Week_24       -97.78     964.44  -0.101   0.9217  
## Week_25      -511.91     962.32  -0.532   0.6092  
## Week_26      -239.44     967.11  -0.248   0.8107  
## Week_27      2769.34    1839.58   1.505   0.1706  
## Week_28       421.86    1452.31   0.290   0.7788  
## Week_29      -188.05    1108.06  -0.170   0.8695  
## Week_30     -1249.50    1486.27  -0.841   0.4249  
## Week_31       -36.94    1227.15  -0.030   0.9767  
## Week_32      -562.77     864.84  -0.651   0.5335  
## Week_33        13.79     887.29   0.016   0.9880  
## Week_34       706.33    1508.98   0.468   0.6522  
## Week_35       463.58     917.83   0.505   0.6271  
## Week_36       140.17    1003.16   0.140   0.8923  
## Week_37     -1448.15    1231.09  -1.176   0.2733  
## Week_38      1112.12    1188.50   0.936   0.3768  
## Week_39     -4316.63    1688.80  -2.556   0.0339 *
## Week_40       965.42    1181.41   0.817   0.4375  
## Week_41      1155.50    1102.94   1.048   0.3254  
## Week_42      1907.43    1098.55   1.736   0.1207  
## Week_43      1104.76    1018.22   1.085   0.3095  
## Week_44       591.90     723.18   0.818   0.4368  
## Week_45     -3018.99    2001.00  -1.509   0.1698  
## Week_46      1702.88    1004.55   1.695   0.1285  
## Week_47       437.14     542.46   0.806   0.4436  
## Week_48        62.91     689.08   0.091   0.9295  
## Week_49       -86.33     472.96  -0.183   0.8597  
## Week_50      -659.45     471.48  -1.399   0.1995  
## Week_51      -430.40     551.36  -0.781   0.4575  
## Week_52       -77.63     694.82  -0.112   0.9138  
## Week_53      -250.63     461.09  -0.544   0.6016  
## Week_1        120.19     529.97   0.227   0.8263  
## Week_2        815.66     650.82   1.253   0.2455  
## Week_3       -465.18     584.69  -0.796   0.4492  
## Week_4         19.45     861.25   0.023   0.9825  
## Week_5       -664.70     536.96  -1.238   0.2509  
## Week_6       -192.77     648.26  -0.297   0.7738  
## Week_7        633.04     811.99   0.780   0.4581  
## Week_8       -728.60     916.47  -0.795   0.4496  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6035 on 8 degrees of freedom
## Multiple R-squared:  0.8788, Adjusted R-squared:  0.07615 
## F-statistic: 1.095 on 53 and 8 DF,  p-value: 0.4872

## [1] "Results for crop: Grapes"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -12448.7  -3502.3    193.7   3786.4  13234.4 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 112133.30   80399.57   1.395  0.20061   
## Week_9       -2793.84    1822.48  -1.533  0.16382   
## Week_10      -2351.08    2152.81  -1.092  0.30658   
## Week_11      -4337.65    2998.24  -1.447  0.18599   
## Week_12       2048.41    2056.35   0.996  0.34835   
## Week_13      -2532.43    3341.96  -0.758  0.47032   
## Week_14      -4707.17    3715.65  -1.267  0.24084   
## Week_15      11230.72    2998.32   3.746  0.00566 **
## Week_16       9815.58    3935.75   2.494  0.03729 * 
## Week_17       9466.78    3691.23   2.565  0.03340 * 
## Week_18       7928.27    3560.13   2.227  0.05656 . 
## Week_19      -1128.59    2479.66  -0.455  0.66111   
## Week_20        856.61    2404.60   0.356  0.73087   
## Week_21      -7926.60    3292.79  -2.407  0.04269 * 
## Week_22       -253.20    2119.97  -0.119  0.90787   
## Week_23      -4197.76    1945.14  -2.158  0.06298 . 
## Week_24      -1847.94    2138.57  -0.864  0.41269   
## Week_25      -1731.49    2133.86  -0.811  0.44059   
## Week_26       1874.95    2144.48   0.874  0.40743   
## Week_27       6735.39    4079.11   1.651  0.13731   
## Week_28      -3863.43    3220.37  -1.200  0.26458   
## Week_29       1611.31    2457.02   0.656  0.53036   
## Week_30      -7912.49    3295.68  -2.401  0.04312 * 
## Week_31      -2952.77    2721.10  -1.085  0.30947   
## Week_32       -673.64    1917.71  -0.351  0.73445   
## Week_33        228.80    1967.50   0.116  0.91029   
## Week_34       3408.61    3346.04   1.019  0.33816   
## Week_35       4223.16    2035.20   2.075  0.07166 . 
## Week_36       2930.23    2224.44   1.317  0.22422   
## Week_37        663.77    2729.84   0.243  0.81400   
## Week_38       3236.61    2635.40   1.228  0.25430   
## Week_39     -10232.13    3744.77  -2.732  0.02575 * 
## Week_40       1769.04    2619.69   0.675  0.51853   
## Week_41      -3185.95    2445.69  -1.303  0.22893   
## Week_42       -450.06    2435.94  -0.185  0.85802   
## Week_43       -672.24    2257.82  -0.298  0.77349   
## Week_44       -932.16    1603.59  -0.581  0.57705   
## Week_45     -11598.72    4437.05  -2.614  0.03093 * 
## Week_46       2073.12    2227.50   0.931  0.37924   
## Week_47       1072.76    1202.85   0.892  0.39851   
## Week_48      -2547.14    1527.98  -1.667  0.13407   
## Week_49        -43.11    1048.76  -0.041  0.96822   
## Week_50        339.86    1045.46   0.325  0.75346   
## Week_51      -2059.93    1222.60  -1.685  0.13050   
## Week_52       1596.31    1540.72   1.036  0.33046   
## Week_53      -1967.42    1022.44  -1.924  0.09052 . 
## Week_1         666.10    1175.16   0.567  0.58639   
## Week_2        2095.77    1443.14   1.452  0.18450   
## Week_3        2129.65    1296.50   1.643  0.13909   
## Week_4       -4412.18    1909.76  -2.310  0.04966 * 
## Week_5         964.84    1190.67   0.810  0.44119   
## Week_6        1711.69    1437.45   1.191  0.26787   
## Week_7        4290.38    1800.53   2.383  0.04435 * 
## Week_8       -4679.71    2032.21  -2.303  0.05025 . 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 13380 on 8 degrees of freedom
## Multiple R-squared:  0.9131, Adjusted R-squared:  0.3377 
## F-statistic: 1.587 on 53 and 8 DF,  p-value: 0.2513

## [1] "Results for crop: Raspberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -8245.9 -2322.8    58.6  2340.2  9916.1 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)
## (Intercept) -20164.05   57522.31  -0.351    0.735
## Week_9       -1077.69    1303.91  -0.827    0.432
## Week_10       1056.12    1540.24   0.686    0.512
## Week_11        650.51    2145.11   0.303    0.769
## Week_12        253.29    1471.23   0.172    0.868
## Week_13      -3572.28    2391.02  -1.494    0.174
## Week_14        760.92    2658.38   0.286    0.782
## Week_15       3945.94    2145.16   1.839    0.103
## Week_16       3105.62    2815.85   1.103    0.302
## Week_17       -189.49    2640.91  -0.072    0.945
## Week_18       -145.33    2547.11  -0.057    0.956
## Week_19        697.69    1774.09   0.393    0.704
## Week_20      -1048.36    1720.38  -0.609    0.559
## Week_21        767.26    2355.84   0.326    0.753
## Week_22       2097.25    1516.74   1.383    0.204
## Week_23       -960.54    1391.66  -0.690    0.510
## Week_24       1240.71    1530.05   0.811    0.441
## Week_25        -70.60    1526.68  -0.046    0.964
## Week_26       1171.28    1534.28   0.763    0.467
## Week_27       -586.00    2918.42  -0.201    0.846
## Week_28      -1486.37    2304.03  -0.645    0.537
## Week_29       1114.77    1757.89   0.634    0.544
## Week_30      -1533.22    2357.92  -0.650    0.534
## Week_31       -578.17    1946.82  -0.297    0.774
## Week_32       1012.67    1372.03   0.738    0.482
## Week_33      -1083.45    1407.66  -0.770    0.464
## Week_34       1372.22    2393.94   0.573    0.582
## Week_35       -767.41    1456.10  -0.527    0.612
## Week_36       1072.17    1591.48   0.674    0.519
## Week_37       3598.08    1953.08   1.842    0.103
## Week_38      -1051.10    1885.51  -0.557    0.592
## Week_39        435.99    2679.22   0.163    0.875
## Week_40       -306.03    1874.27  -0.163    0.874
## Week_41      -1737.74    1749.78  -0.993    0.350
## Week_42      -1425.30    1742.81  -0.818    0.437
## Week_43      -1388.64    1615.37  -0.860    0.415
## Week_44        472.81    1147.29   0.412    0.691
## Week_45      -1791.41    3174.51  -0.564    0.588
## Week_46      -1907.65    1593.68  -1.197    0.266
## Week_47        851.79     860.59   0.990    0.351
## Week_48      -1133.27    1093.20  -1.037    0.330
## Week_49       -454.77     750.34  -0.606    0.561
## Week_50        225.69     747.98   0.302    0.771
## Week_51      -1081.94     874.71  -1.237    0.251
## Week_52       1382.83    1102.31   1.254    0.245
## Week_53       -711.16     731.51  -0.972    0.359
## Week_1        -305.22     840.78  -0.363    0.726
## Week_2        1226.81    1032.50   1.188    0.269
## Week_3          12.91     927.59   0.014    0.989
## Week_4         -38.37    1366.35  -0.028    0.978
## Week_5         325.63     851.87   0.382    0.712
## Week_6         247.79    1028.43   0.241    0.816
## Week_7        1885.25    1288.20   1.463    0.181
## Week_8        -603.88    1453.95  -0.415    0.689
## 
## Residual standard error: 9574 on 8 degrees of freedom
## Multiple R-squared:  0.8684, Adjusted R-squared:  -0.003459 
## F-statistic: 0.996 on 53 and 8 DF,  p-value: 0.5558

## [1] "Results for crop: Strawberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -9605.5 -3589.4  -453.4  3413.7 13219.0 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -117130.74   84447.31  -1.387   0.2029  
## Week_9        -1358.47    1914.24  -0.710   0.4981  
## Week_10       -1332.42    2261.20  -0.589   0.5720  
## Week_11       -4123.16    3149.19  -1.309   0.2268  
## Week_12        3031.39    2159.88   1.404   0.1981  
## Week_13        1393.36    3510.21   0.397   0.7018  
## Week_14       -6796.86    3902.71  -1.742   0.1198  
## Week_15        7772.94    3149.27   2.468   0.0388 *
## Week_16        3218.83    4133.90   0.779   0.4586  
## Week_17        4831.33    3877.07   1.246   0.2480  
## Week_18        3897.67    3739.36   1.042   0.3277  
## Week_19         614.63    2604.50   0.236   0.8194  
## Week_20        1844.77    2525.66   0.730   0.4860  
## Week_21       -4366.74    3458.57  -1.263   0.2423  
## Week_22        -808.69    2226.70  -0.363   0.7259  
## Week_23       -1902.70    2043.07  -0.931   0.3789  
## Week_24       -1976.95    2246.24  -0.880   0.4045  
## Week_25       -2340.67    2241.29  -1.044   0.3269  
## Week_26        3866.26    2252.45   1.716   0.1244  
## Week_27        1853.72    4284.48   0.433   0.6767  
## Week_28        2568.20    3382.50   0.759   0.4695  
## Week_29        -689.31    2580.72  -0.267   0.7961  
## Week_30       -4137.12    3461.61  -1.195   0.2663  
## Week_31        2183.53    2858.09   0.764   0.4668  
## Week_32        -626.12    2014.25  -0.311   0.7639  
## Week_33       -1642.49    2066.56  -0.795   0.4497  
## Week_34        5709.57    3514.50   1.625   0.1429  
## Week_35        2503.00    2137.67   1.171   0.2753  
## Week_36         -19.91    2336.43  -0.009   0.9934  
## Week_37        1057.13    2867.27   0.369   0.7219  
## Week_38        1709.18    2768.08   0.617   0.5541  
## Week_39       -5569.75    3933.30  -1.416   0.1945  
## Week_40        1667.97    2751.58   0.606   0.5612  
## Week_41        -685.59    2568.82  -0.267   0.7963  
## Week_42        1152.67    2558.58   0.451   0.6643  
## Week_43        1132.52    2371.49   0.478   0.6457  
## Week_44         544.74    1684.32   0.323   0.7547  
## Week_45       -5784.71    4660.43  -1.241   0.2497  
## Week_46        3999.55    2339.65   1.709   0.1257  
## Week_47         828.02    1263.41   0.655   0.5306  
## Week_48       -1276.81    1604.90  -0.796   0.4492  
## Week_49       -1641.10    1101.56  -1.490   0.1746  
## Week_50         165.23    1098.10   0.150   0.8841  
## Week_51       -1140.50    1284.15  -0.888   0.4004  
## Week_52         610.44    1618.29   0.377   0.7158  
## Week_53        -950.05    1073.91  -0.885   0.4021  
## Week_1          430.45    1234.33   0.349   0.7363  
## Week_2          432.32    1515.80   0.285   0.7827  
## Week_3         1246.78    1361.77   0.916   0.3867  
## Week_4        -2026.16    2005.91  -1.010   0.3420  
## Week_5          571.82    1250.61   0.457   0.6597  
## Week_6          166.74    1509.82   0.110   0.9148  
## Week_7         1629.22    1891.18   0.861   0.4140  
## Week_8        -4098.43    2134.52  -1.920   0.0911 .
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 14060 on 8 degrees of freedom
## Multiple R-squared:  0.9329, Adjusted R-squared:  0.4884 
## F-statistic: 2.099 on 53 and 8 DF,  p-value: 0.1326